Why AM an EUISKO appear to work.
Artificial Intelligence
The use of design descriptions in automated diagnosis
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
AI Magazine
The society of mind
The Hearsay-II Speech-Understanding System: Integrating Knowledge to Resolve Uncertainty
ACM Computing Surveys (CSUR)
A Computer Model of Skill Acquisition
A Computer Model of Skill Acquisition
Human Problem Solving
Conceptual graphs for the analysis and generation of sentences
IBM Journal of Research and Development
Can model-based and case-based expert systems operate together?
ITC '98 Proceedings of the 1998 IEEE International Test Conference
A dual-system variable-grain cooperative coevolutionary algorithm: satellite-module layout design
IEEE Transactions on Evolutionary Computation
Cognitive architectures for conceptual structures
ICCS'11 Proceedings of the 19th international conference on Conceptual structures for discovering knowledge
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We articulate the three major findings of AI to date: (1) The Knowledge Principle: if a program is to perform a complex task well, it must know a great deal about the world in which it operates. (2) A plausible extension of that principle, called the Breadth Hypothesis: there are two additional abilities necessary for intelligent behavior in unexpected situations: falling back on increasingly general knowledge, and analogizing to specific but farflung knowledge. (3) AI as Empirical Inquiry: we must test our ideas experimentally, on large problems. Each of these three hypotheses proposes a particular threshold to cross, which leads to a qualitative change in emergent intelligence. Together, they determine a direction for future AI research.